This paper investigates how commonly prescribed pharmacologic treatments for Alzheimer’s disease (AD) affect
Event-Related Potential (ERP) biomarkers as tools for predicting AD conversion in individuals with Mild Cognitive
Impairment (MCI). We gathered baseline ERP data from two MCI groups (those taking AD medications and those not)
and later determined which subjects developed AD (Convert->AD) and which subjects remained cognitively stable (Stable).
We utilized a previously developed and validated multivariate system of ERP components to measure medication effects
among these four subgroups. Discriminant analysis produced classification scores for each individual as a measure
of similarity to each clinical group (Convert->AD, Stable), and we found a large significant main Group effect but no
main AD Medications effect and no Group by Medications interaction. This suggested AD medications have negligible
influence on this set of ERP components as weighted markers of disease progression. These results provide practical information
to those using ERP measures as a biomarker to identify and track AD in individuals in a clinical or research setting.
Keywords: Alzheimer’ s disease (AD), AD drug treatments, biomarker, discriminant analysis, EEG, event-related potentials
(ERP), mild cognitive impairment (MCI), neurophysiology, prediction, principal components analysis (PCA).
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